Outgrowing Jira’s Sprint Reports? Here are 2 alternatives you should consider.
Every Scrum engineering team needs to report on their sprints.
When it’s done right, sprint reporting allows Scrum teams and stakeholders – like PMs, POs, engineering managers and leaders – to:
- Understand project progress
- Monitor team performance
- Assess roadblocks
- Review metrics
- Make informed, timely decisions
- Set realistic goals
That’s not an exhaustive list, but it gives you an idea of how pivotal good sprint reporting is. It’s a critical part of the feedback loop.
But many Agile teams struggle to get sprint reporting right.
Sprint reports are often:
- Lacking context
- Lacking commentary
- Lacking concision
- Misaligned (or unaligned) with team goals
- Overloaded and overwhelmin
The problem is that we typically have to choose between creating reports that are genuinely useful (but take time to get right), or reports that are fast to make (but lack utility).
Many teams achieve the latter with Jira’s Sprint Reports, so today, I want to look at how they work, and a couple of alternatives that remove the need to make the decision between utility and speed.
Jira’s Sprint Reports
Jira has long been a trusted name, providing countless software development teams with tools for agile project management.
One of those tools is the Sprint Report tool.
For those uninitiated, the Jira Sprint Report is available via Projects > Reports > Sprint Report, it aims to support team retrospectives and periodic progress checks.
Key elements of their report include the sprint burndown chart summary and the status report (of completed and incomplete issues).
Why Jira’s Sprint Reports leave teams behind
A noteworthy limitation is the report's rigidity. It measures progress predominantly via story points. If your team doesn’t work with story points? Well, you're facing a wall.
On the surface, Jira's Sprint Report might seem adequately equipped to do the job it says on the tin. Its integration within Jira offers convenience – it’s there, ready for action.
Problem is, Jira sprint reports don’t actually surface the insights people need to know.
- Detail drought. The reports often provide a surface-level view, lacking the granularity that teams may require for effective retrospectives.
- Story Points Centricity. Its inherent design leans heavily on story points, sidelining other potential metrics of progress. The reports miss out on offering a complete picture, making it challenging to understand team velocities or how resources are allocated across projects.
- Reliance on Issue-Level Summaries. Teams are left navigating through individual issue summaries without an overarching narrative.
Because sprint reports are such a central part of the operational feedback loop in engineering, the impact of half-baked reports spread far and wide, impacting different people in different ways. The impact ripples through team dynamics, productivity, morale, and results – it always finds its way back to the bottom line.
- Wasted Time and Resources: If the core insights aren't immediately apparent, teams can find themselves analyzing the data for longer, often drawing varied interpretations from the same information. This not only consumes time but can lead to disjointed efforts.
- Strategic Disconnect: Reports that don't tie directly into overarching objectives can divert teams from the primary mission. A lack of granular insight into individual projects can muddle decision-making processes and resource allocation.
- Risk of Ambiguity: Raw, unprocessed data can easily be misconstrued. Different team members might derive different, sometimes conflicting, interpretations, leading to potential conflicts and missteps.
- Blurred Accountability: Without clear, consistent data interpretation, holding individuals or teams accountable becomes a challenge. It's even more complicated when these reports don't align with strategic and delivery targets.
- Reactive, Not Proactive, Decision Making: Ambiguous reports hinder our ability to identify and act upon challenges proactively. Moreover, without clarity on successes, it becomes difficult to replicate them or understand the driving factors behind them.
- Loss of Actionable Insights: In the shuffle of data, the actionable steps often get lost, making it hard for teams to take definitive, impactful actions.
Inefficient sprint reports touch the very core of team dynamics, planning, and execution. As teams push boundaries, innovate, and adapt to the demanding pace of 2023, the need for effective, insightful sprint reports has never been greater.
Alternative #1: Use Jira's Reports as a starting point
While Jira offers a foundational layer for agile reporting, many teams acknowledge the gaps in its service. It’s an entirely reasonable solution to bridge those gaps manually.
Manually supplementing Jira's reports often involves gathering data from other tools or internal sources and integrating them into the native Jira report.
For example, teams might extract other types of reports, like the Velocity Chart, from Jira, marrying it with anecdotal team feedback to provide context.
Of course, this approach has obvious drawbacks.
First, it’s time (and resource) intensive. And since reporting is not innately value-generating, there’s an opportunity cost to the time reporting takes, too. The time alone is substantial – if it takes someone two hours to create a report, plus an hour chasing updates and data gaps, that’s 156 hours annually. If they earn $75,000, that’s costing you $5,600 a year, If you have 10 teams, that’s $56,000. Better make it count, then.
Second, it’s subject to human error. A manual process is vulnerable to inconsistencies, be it in data interpretation or presentation, leading to potential discrepancies in decision-making. And despite best efforts, a manually supplemented report often fails to capture the intuitive insights that specialised tools bring.
But it’s entirely possible to make this work.
For this to be efficient, the right data and context needs to be readily available to minimise the time to create the report. There should be a repeatable, predictable process to generate the report on a weekly process, without taking up loads of time (and therefore resources), taking engineers out of their flow to provide updates, and avoiding the opportunity cost.
Alternative #2: Stepsize AI
The second option solves the problems with both Jira Sprint Reports, and the potential problems of the first alternative of manually supplementing them.
The nature of sprint reporting has meant that we’ve traditionally had to accept the trade-off between the usefulness of our reports, or the time and resource we have to burn to create what we need.
Today, we no longer need to accept this trade-off.
It’s called Stepsize AI, and I’m building it with my team at Stepsize.
Stepsize AI is designed from the ground up to address the shortcomings of traditional reporting systems.
And it works directly with Jira software.
It observes everything happening in the relevant Jira board, and uses AI to develop context, understanding of sprint goals, and form connections between tasks and activities.
It uses this to generate accurate, automatic sprint reports with the perfect amount of context and commentary.
By using this tool, you take advantage of…
- Context-aware AI – it grasps the nuanced context of projects, sub-projects and goals
- Concise, readable updates – data overload is a common occurrence. Stepsize AI curates the insights that matter and conveys them concisely.
- Goal-centric reporting – it innately links your project and sprint progress to objectives
Importantly, it’s built security-first, so you can be sure your data is safe and – of course – never, ever used to train an AI model.
We’ve taken for granted that sprint reporting is going to involve a trade-off of either utility or time-intensivity for long enough.